Over-integration of visual network in major depressive disorder and its association with gene expression profiles

Abstract

Major depressive disorder (MDD) is a common psychiatric condition associated with aberrant functional connectivity in large-scale brain networks. However, it is unclear how the network dysfunction is characterized by imbalance or derangement of network modular interaction in MDD patients and whether this disruption is associated with gene expression profiles. We included 262 MDD patients and 297 healthy controls, embarking on a comprehensive analysis of intrinsic brain activity using resting-state functional magnetic resonance imaging (R-fMRI). We assessed brain network integration by calculating the Participation Coefficient (PC) and conducted an analysis of intra- and inter-modular connections to reveal the dysconnectivity patterns underlying abnormal PC manifestations. Besides, we explored the potential relationship between the above graph theory measures and clinical symptoms severity in MDD. Finally, we sought to uncover the association between aberrant graph theory measures and postmortem gene expression data sourced from the Allen Human Brain Atlas (AHBA). Relative to the controls, alterations in systemic functional connectivity were observed in MDD patients. Specifically, increased PC within the bilateral visual network (VIS) was found, accompanied by elevated functional connectivities (FCs) between VIS and both higher-order networks and Limbic network (Limbic), contrasted by diminished FCs within the VIS and between the VIS and the sensorimotor network (SMN). The clinical correlations indicated positive associations between inter-VIS FCs and depression symptom, whereas negative correlations were noted between intra-VIS FCs with depression symptom and cognitive disfunction. The transcriptional profiles explained 21-23.5% variance of the altered brain network system dysconnectivity pattern, with the most correlated genes enriched in trans-synaptic signaling and ion transport regulation. These results highlight the modular connectome dysfunctions characteristic of MDD and its linkage with gene expression profiles and clinical symptomatology, providing insight into the neurobiological underpinnings and holding potential implications for clinical management and therapeutic interventions in MDD.